On an extended interpretation of linkage disequilibrium in genetic case-control association studies

Thorsten Dickhaus, Stange Jens and Demirhan Haydar
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Stange Jens: Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany
Demirhan Haydar: Hacettepe University, Department of Statistics, Ankara, Turkey

Statistical Applications in Genetics and Molecular Biology, 2015, vol. 14, issue 5, 497-505

Abstract: We are concerned with statistical inference for 2×C×K contingency tables in the context of genetic case-control association studies. Multivariate methods based on asymptotic Gaussianity of vectors of test statistics require information about the asymptotic correlation structure among these test statistics under the global null hypothesis. In the case of C=2, we show that for a wide variety of test statistics this asymptotic correlation structure is given by the standardized linkage disequilibrium matrix of the K loci under investigation. Three popular choices of test statistics are discussed for illustration. In the case of C=3, the standardized composite linkage disequilibrium matrix is the limiting correlation matrix of the K locus-specific Cochran-Armitage trend test statistics.

Keywords: asymptotic Gaussianity; chi-squared statistic; Cochran-Armitage trend test; contingency table; correlation structure; Delta method; Fisher’s exact test; odds ratio (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1515/sagmb-2015-0024

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